The performance of software fault localization techniques is critical to software debugging and the reliability of software. Spectrum-based fault localization (SBFL) and mutation-based fault localization (MBFL) are the two most popular fault localization methods. However, the accuracies of the two methods are still limited. For example, only 10.63% of faults can be detected by inspecting the top 3 suspicious elements reported by Ochiai, which is a famous SBFL technique. Unfortunately, programmers only examine the first few suspicious elements before losing patience. Since the information used in SBFL and MBFL are quite different and complementary, this paper proposes a novel approach by combining spectrum and mutation to improve the fault localization accuracy. First, the faulty program is evaluated by using SBFL, and the potential faulty statements are ranked according to their suspiciousness. Then, mutants of the program are generated and executed by MBFL. Finally, the statements that are ranked in the top tied n by SBFL are evaluated and reranked according to their mutation scores. Experiments are carried on the Defects4J benchmark and the results reveal that the accuracy of the proposed approach outperforms those of the SBFL and MBFL techniques. In terms of the faults located by inspecting the top 1 suspicious elements, the SMFL techniques detect at least 2.36 times more faults than two SBFL techniques (DStar and Ochiai) and detect at least 1.86 times more faults than two MBFL techniques (MUSE and Metallaxis).

Services in Internet of Things (IoT services) are extensions of traditional Web services. Through sensor networks, IoT services can communicate directly with the entities in the physical environment, and even impact them directly. So, because of the influence of the physical environment (such as the time limitation, the resource limitation and the equipment fault probability), features of IoT services are more easily affected by the physical environment than the traditional Web service. In this case, the response time, the service consumption and the fault-tolerant ability become important factors in the performance of the whole IoT system. Therefore, modeling the IoT services detailedly and formally is very important for the analysis and prediction of the performance of the whole IoT system. In this paper, we propose an environment based IoT service modeling framework as well as an ontology of the IoT service and a triple-element model, and advance the corresponding modeling principle. Based on this framework, we proposed a detailed IoT model method, in which the IoT services and their corresponding environment can be described in probabilistic timed automata. The user's desired IoT services features can be described in the temporal logic formula. With our method, the validity of the whole system and the satisfiability of its non-functional constraints can be analyzed detailedly and formally.

Fuzz testing has been successful in finding defects of various software packages. These defects include file parsing, image processing, Internet browsers, and network protocols. However, the quality of the initial seed test cases greatly influences the coverage and defect detection capability of fuzz testing. To address this issue, we propose CSEFuzz, a fuzz testing approach based on symbolic execution for defect detection. First, CSEFuzz generates candidate test cases by symbolic execution and collects coverage information of the test cases. Then, CSEFuzz extracts the test-case templates of the test cases and selects a set of test-case templates according to specific coverage criteria. Finally, CSEFuzz selects test cases according to the selected test-case templates, and the selected test cases are used as initial seed test cases for fuzz testing. Experiments are conducted on 11 open-source programs. The results show that in comparison with afl-cmin, which is the test-case selection command of Kelinci, CSEFuzz with a path coverage criterion reduces the time costs of the initial seed test selection and verification by 94.26%. In addition, compared with afl-cmin, 32 more paths are covered and 16 more defects are detected by CSEFuzz.

To improve the efficiency of fixing bugs, mobile application developers must reproduce bugs reported by testers or users as quickly as possible. In some cases, automated testing tools can help developers reproduce crashes. However, these tools were not designed for reproducing bug reports. They are not efficient at reproducing crashes. To focus testing resources on suspicious widgets, we propose CrPDroid, a fast crash reproduction method for Android applications based on widget hierarchy graphs. First, it builds a widget hierarchy graph by using the project file of the application under test; then, it locates suspicious widgets by analyzing the bug report and the project file of the application under test and calculates the fitness of each widget according to the widget hierarchy graph; finally, it uses the fitness of widgets to guide automated testing to reproduce crashes quickly. To evaluate the effectiveness of CrPDroid, experiments are conducted on real Android application bug reports, and the crash reproduction tool ReCDroid, ReproBot and automated testing tools APE and PUMA are compared with CrPDroid. The experimental results show that CrPDroid successfully reproduces 15 bug reports that cause Android app crashes. In addition, compared with APE, PUMA, ReCDroid, and ReproBot, the average time for CrPDroid to reproduce crashes decreased by 76.87%, 81.94%, 95.58%, and 76.55%, and the total number of operations on suspicious widgets in the same period of testing time increased by 44.07%, 87.57%, 88.70%, and 68.93% on average, respectively.

With the increasing of Web services in Internet, composing existing services for satisfying new requirements has gained daily expanding attentions and interests. Many efforts have been pursued for supporting the essential activities in service composition. However, the existing techniques only focus on passive services which are waiting there for being discovered and invoked, we argue that it might be more attractive when Web services become active entities (service agent) distributed in Internet which can recognize the newly emergent requirements and compete with others for realize (part of) the requirements. Sometimes, more than one service agents have to collaborate to satisfy the requirements. That could be called as the requirement driven agent collaboration. This paper proposes a preliminary model for the requirement driven agent collaboration based on a functional ontology and the automated mechanism design